Online search engines have become an increasingly important tool for conducting research or navigating documents accessible via the Internet. Often, the online search engines perform a matching process for detecting possible documents, or text within those documents, that utilizes a query submitted by a user. Initially, the matching process, offered by conventional online search engines such as those maintained by Google or Yahoo, allow the user to specify one or more keywords in the query to describe information that s/he is looking for. Next, the conventional online search engine proceeds to find all documents that contain exact matches of the keywords, although these documents typically do not provide relevant or meaningful results in response to the query.
Present conventional online search engines are limited in that they do not recognize words in the searched documents corresponding to keywords in the query beyond the exact matches produced by the matching process. Also, conventional online search engines are limited because a user is restricted to keywords in a query that are to be matched, and thus, do not allow the user to precisely express the information desired, if unknown. Accordingly, implementing a natural language search engine to recognize semantic relationships between keywords of a query and words in searched documents would uniquely increase the accuracy of the search results.